The purpose of this module is to explore academic integrity and its role in nursing education and the competency of nurses entering the profession.
By the completion of this activity, the nurse will be able to:
- define academic integrity and plagiarism in the academic setting
- explain the implications of academic integrity for nursing students and graduate nurses
- consider how the nurse educator can recognize plagiarism and other acts of academic integrity violations in nursing students
- discuss the management of academic integrity and plagiarism in nursing programs
Academic integrity (AI) and plagiarism among students are of concern to educators in today’s higher education setting. For nurse educators, the stakes are significantly higher than many other programs; as Rani and colleagues (2019) noted, “academically dishonest nursing students are more likely to commit dishonest acts in clinical practice” (p. 52). Krueger’s (2014) study of 336 nursing students that committed academic integrity violations found a positive correlation between the classroom and clinical dishonesty. Nurse educators spend a significant amount of their time ensuring that work turned in by students is original, helping to establish that each student has achieved the competencies of the program. Once an AI violation or plagiarized assignment is discovered, nurse educators must apply consistent and fair policies as developed by the academic institution (Rani et al., 2019). This module will explore the implications of AI, the reasons that students cheat, and how to manage the concerns.
What is Plagiarism or Academic Integrity?
Professor Donald McCabe, the founding father of the term “academic integrity”, first defined the term in 1992 as a commitment to five fundamental values: honesty, trust, fairness, respect, and responsibility. AI should be the foundation of nursing, the most trusted profession for 18 years in a row according to Gallup polls (The Center for Academic Integrity, [CAI], 2014; Reinhart, 2020). A student who fails to perform their own work during a nursing program is likely to compromise their acquisition of necessary knowledge and skills required to manage patient care. Further, ethical standards that are ignored during academia leads to a lack of ethical standards in clinical practice, which is contrary to nurses’ basic mantra (Rani et al., 2019). Plagiarism is a specific behavior that indicates a lack of AI, and an issue that requires particular attention in academics. According to Douglas and Watt (2019), plagiarism is the act of misrepresenting as one’s own original work the ideas, interpretations, words, or creative works of another either intentionally or unintentionally. These include published and unpublished documents, designs, music, sounds, images, photographs, computer codes, and ideas gained through working in a group. These ideas, interpretations, words, or works may be found in print and/or electronic media (p. 74).
Categories of plagiarism include the following:
- Copy-and-pasting includes small or large pieces of text from another source (student work, book, article, webpage, or previous work) and pasting it into the student’s own assignment. Copy-and-pasting does not involve citation of the original work and is likely intentional plagiarism. There may be a slight alteration to the work, such as changing out two or three words within the text, or it may be verbatim. When the student reuses their own work, it is known as self-plagiarism. This type of plagiarism may be handled differently within an institution than other forms of plagiarism. For instance, they may allow the student to cite themselves from a previous paper or dissertation. Students may confuse copy-and-pasting with integrating a direct quote. Faculty may need to educate the student on formatting direct quotes and offering proper citation yet explaining that a paper should not be primarily made up of information that has been copy-and-pasted.
- Minimalist paraphrasing includes a student changing only a few words within the original text. This type of plagiarism may also be referred to as “word-smithing”, because the student may rearrange words to confuse Turnitin (TII) or other anti-plagiarism software and the faculty member reviewing the work. TII is software that universities or individuals can purchase that compares student work to websites, other student papers, and articles across multiple databases.
- Patchworking includes the use of multiple sources that are combined into a new, original assignment. An example would be attaining four or five previous student’s papers, and putting parts of each into a single paper, claiming it as original work. Since the student did not create original text, this is considered a sophisticated form of plagiarism.
- A twisted grapevine involves attributing information to the wrong author or the inappropriate use of secondary sources. An example would be an assignment that requires data from the past five years. Rather than a student taking the time to find that data, they find data that is 10-15 years old instead and change the date on the resource to meet the assignment requirement. Alternatively, a student may use a newer article with secondary information. Instead of appropriately citing the information with the original source, they cite the newer article, resulting in a lack of credit to the original author or source (Goodwin & McCarthy, 2020).
Modern day students are surrounded by electronic information and resources, which often tempt them to use other people’s words or content to develop their own work. There may be confusion over integrating evidence into a paper or presentation and misrepresenting the other person’s work as the student’s own. Individuals who plagiarize not only harm the person they are taking work from, but they also harm themselves by failing to engage in the educational process and learn the materials as intended by their faculty and program curriculum (Henslee et al., 2015).
Ghostwriters may be hired to produce an assignment for a student according to the guidelines within their course. The student accepts credit for a specific paper or assignment that is created for a fee by the contracted ghostwriter. This kind of practice has been used in literature for many years but is considered plagiarism by academic institutions. Undergraduate students often sell their previous work, laboratory journals, or other assignments that may be copied verbatim by the purchasing student. When ghost writers initially entered the internet, anti-plagiarism software such as TII were able to detect the similarities between papers, but suppliers of these papers now typically claim they can produce papers that are undetectable by anti-plagiarism software. There are millions of these services available with a Google search and may be tempting to students that are struggling to produce required assignments. Ghostwriting is particularly difficult to prove, and faculty may not pick up on these submissions as easily as other types of plagiarism. Getting to know the student and their individual writing style can often aid in recognizing the student who utilizes a ghostwriter (Singh & Remenyi, 2016).
In addition to the use of ghostwriters, additional AI violations can occur such as online tutoring sites that advertise themselves as a source for student success and the use of peer work. The following are considered potential AI violations that students may attempt:
- collusion or working together on an assignment meant to be an individual submission;
- copying another person’s work using an online tutoring service, ghostwriter, or the use of another student’s work;
- bribing a professor or another student with money, goods, or services;
- misrepresentation, including lying to an instructor or when confronted with an AI violation;
- duplicate submission by using the same work for two different classes without permission from both instructors;
- academic misconduct including obtaining a copy of a test prior to administration; distributing a test prior to administration, whether free of charge or for a fee; encouraging others to obtain a copy of a test before it is administered; changing grades in a grade book, computer, or an assignment; or continuing to work on a test after the time limit is reached;
- unauthorized use of a calculator or computer program when told it is disallowed; or
- disruptive behavior such as failure to silence a cell phone, posting inappropriate material online related to a course, talking or texting during a lecture, or disrespecting a professor or another student online or in class (St. Petersburg College, n.d.).
Students cannot be successful in their academic journey without integrity in their work (Gallant, 2018). Most students recognize the need to maintain integrity within their academic program yet may find themselves in situations where their standards are compromised. In a study exploring students’ perceptions of academic integrity, nursing students reported someone with AI as being trustworthy. The same study found that those with a high degree of integrity in their academic work are seen as professional, while those with a low degree of integrity in their work are seen as a potential danger to patients in the clinical setting (CAI, 2014; Rani et al., 2019). Clearly, nursing students realize the importance of AI in the completion of their assignments and required activities within their programs, so why do nursing students violate AI, including plagiarism? A 2011 study by Babu and colleagues conducted a similar study among 166 undergraduate medical students in India. All participants reported having been involved in at least one act of academic dishonesty. The same study explored the reasons behind those acts, which included pressure to succeed academically, lack of adequate time to study, the fear of losing status among student peers, and the relative success acquired through cheating toward the completion of their academic program (Babu et al., 2011; Rani et al., 2019). Many institutions identify AI only in negative terms and focus on prohibiting behaviors rather than framing AI as positive and practical. The values of AI, as identified by McCabe, provide the direction and guidance that many students require to practice AI (CAI, 2014). Most foundational of these may be honesty. Honesty is a prerequisite for the development of trust, fairness, responsibility, and respect for others. Thomas Jefferson noted that “honesty is the first chapter in the book of wisdom”. Student or faculty behavior that is dishonest can jeopardize an academic institution, tarnish its reputation, and decrease the value of conferred degrees. Students who graduate from an organization without acquiring the expected knowledge, skills, and attitudes subsequently enter the community and professional realm with limited skills; reflecting poorly on their academic institution (CAI, 2014).
Even the most highly regarded institutions can be marred by reported cheating. Harvard was involved in a cheating scandal in 2012; approximately 125 students cheated on a take-home final examination in their government class. One of the teaching fellows noticed a similarity among some of the examinations upon grading and found that nearly half of the students enrolled in this class had been involved in the incident. About 70% of the students involved in the cheating scandal were forced to withdraw from the university. The most interesting aspect of this case was that the class in question already had a reputation for being easy, as the grades were determined by four take-home exams, including the final. Students were permitted to use their books, the internet, and open notes when completing the exam, but were not allowed to collaborate with one another. Many complained that the questions on the final exam were confusing; the faculty had clarified three questions by email during the exam period. During the school’s internal investigation of this case, students were required to submit written explanations of their answers on the exam and the classmates they collaborated with. Many of the students provided the names of their peers who were part of the collaboration. Faculty were required to clarify their collaboration policies in future classes, noting that better communication regarding expectations may be required for students. Among the articles about this scandal, it was noted that gaps existed in the students’ perceptions related to expectations regarding their performance. Many students suggested the course was not taken seriously due to the fact that the faculty did not expect attendance at lectures. Graduate teaching assistants were responsible for most of the instruction, and students were often confused by the exam instructions allowing the use of their textbooks, the internet, and open-notes, but not allowing them to discuss the exam with their classmates (Boston Globe, 2012; Perez-Pena & Bigood, 2012). Orr (2018) noted that ethical practices and principles should be implemented across the curricula to direct students toward an intentional and transformative learning experience. By ensuring that students understand a culture of academic integrity exists, there is less likelihood of cheating. As within the Harvard case, consistent and expedient action for all incidents of AI demonstrates a unified focus on student performance.
Studies have shown that 47-60% of all nursing students plagiarize within their assignments, and despite the availability of citation software, they may not credit original sources for their work. Their plagiarism or AI infractions may be intentional or unintentional, as students may struggle to recognize when they are plagiarizing. Intentional plagiarism occurs when students feel pressured to complete assignments by the established deadlines, or if they are struggling to comprehend the topic. Unintentional plagiarism is more often the result of a lack of understanding regarding academic writing and the rules associated with citing references. Online cutting and pasting may result from bad habits; students pull information from blogs, websites, or articles without citing or paraphrasing, resulting in plagiarism. Many students may not even realize that they are plagiarizing and stealing other people’s intellectual information, so unintentional plagiarism can be reduced through thorough education regarding how to properly utilize other’s work and then cite it properly. Students should be given a clear and concise definition of plagiarism and how to avoid it, as well as other ways to promote AI across the curricula. Schools may be well served to develop tools to establish these clear expectations for online and face-to-face students from the start. Avoiding plagiarism is not time-consuming, nor is it difficult but must be consistent and deliberate (Goodwin & McCarthy, 2020).
Nurse Educators Role with AI Violations
Faculty typically have the option of two paths to follow when faced with plagiarism. They may either ignore it and risk rewarding the student for turning in work that is not their own or move through the institution’s process to penalize the student for plagiarism. In a study to determine potential interventions for plagiarism, Henslee and colleagues (2015) compared an online tutorial that students completed to recognize behaviors that constituted plagiarism and how to avoid it. In the study, they compared the online tutorial to pre-recorded lecture through a one-credit hour course with the same content. The two groups had similar results with plagiarism noting that students either did not plagiarize at all, or they had one episode of plagiarism after taking the course or completing the tutorial in the subsequent quizzes or assignments. They also noted that students who took both courses performed similarly in retaking quizzes to improve their grades or copying and pasting information in written assignments. The association of plagiarism and multiple quiz attempts led the authors to hypothesize that the students do not fully understand the content and require more attempts to master the information. The cheating likely occurs to avoid punishment or earn a degree. Students who are mastery oriented are more likely to have an intrinsic drive to learn the material and thus perform better in academic assignments or quizzes (Henslee et al., 2015). As with the Harvard incident, it is incumbent upon institutions, and ultimately faculty, to include clear directives within the syllabus or individual assignments to establish clear expectations and protect the integrity of the assignment if brought into question with AI violations. Literature suggests that students should be educated on AI violations within their first year of education to fully understand the implications and to promote good writing habits early in their education. Clear policies and training should also be developed to guide the student in maintaining AI throughout their academic and then professional career (Goodwin & McCarthy, 2020). Additionally, faculty should strive to inspire students to become lifelong learners and delve into their assignments, mastering the concepts, and applying the information through assigned work. Cutting and pasting another individual’s work, or a similar AI violation, does not promote student engagement or acquisition of required knowledge. Faculty should provide learning opportunities that are engaging, interesting, and rewarding to encourage students to participate. Positive experiences as learning opportunities may decrease the motivation to cheat. Faculty can intentionally design their courses to deter AI violations and develop classroom expectations that promote AI (Gallant, 2018).
Most schools encourage faculty to utilize anti-plagiarism software such as TII to assist them in readily identifying discrepancies. Faculty training on the software is needed to ensure an accurate interpretation of the generated reports. A TII report that indicates a similarity to websites, or other student papers, does not necessarily mean the student is guilty of an infraction. Schools should develop training and policies on the interpretation and implementation of sanctions based on TII or other anti-plagiarism tools (Singh & Remenyi, 2016).
The use of part-time faculty or visiting professors can be a concern for institutions. Most colleges, particularly community colleges or smaller institutions, employ many part-time faculty. Developing assignments that promote integrity requires intention, time, and effort from the instructor, and part-time faculty may be less able to devote the time to create these learning opportunities as many work full time in other professions or may not fully grasp the institution’s policies. These faculty may be limited in their knowledge and skills to develop assignments that reduce cheating, including active learning pedagogies such as problem-based learning, case studies, team-based learning, or peer instruction. If part-time faculty are expected to champion AI, they must have support from institutional leadership that includes training and professional development (Gallant, 2018).
Managing as a Teachable Moment
Acts of plagiarism may be unintentional and determining intent can be difficult. Most schools provide the student with an opportunity to learn from the experience and assume the act of AI was unintentional initially. This learning experience may be called a teachable moment in which the faculty meets with the student, explains the violation, and allows them to resubmit the assignment with little to no penalty or recording of the offense. Students are typically grateful for the opportunity and may avoid repeating the behavior in the future. Georgia Tech moved from a punitive perspective of “I caught you”, to a teaching perspective of “I taught you” to improve their student’s writing. This school utilizes a TII draft submission resource that allows students to check their paper prior to final submission and make suggested corrections in citations and paraphrasing to decrease unintentional plagiarism (Spezzo, 2018). Several studies support the use of TII as a tool to improve student writing (Graham—Matheson & Starr, 2013; Rolfe, 2011).
Managing AI Violations
When AI violations occur, schools may allow faculty to manage the situations independently and determine whether the event is a teachable moment for the student, an assignment failure, or a course failure. While allowing the professors in these schools the professional autonomy to manage their students how they see fit, some faculty may find it easier to overlook the infraction altogether and grade the plagiarized assignment or allow the student to resubmit with no record of the event. A vital concern, both legally and ethically, is that all students are investigated fairly and sanctioned consistently, and this may not occur in schools that allow faculty to manage the cases independently. For this reason, many schools have opted instead for support from leaders such as the department chair or dean to provide guidance and consistency in sanctions, ensuring policies are adhered to similarly in all courses. Some institutions have developed an AI panel to handle all suspected violations and manage a database that tracks student behaviors and recognizes repeat or escalating offenders. A student may escalate to a school expulsion with repeat violations (Gallant, 2018).
Let’s explore a case study that may be helpful in considering AI violation policies. Student A submits a paper that is 50% plagiarized with no citations or paraphrasing; the student simply cut and paste the work from a website. While meeting with the student, the faculty explains how to paraphrase and cite, ultimately allowing the student another opportunity to submit. The student proceeds with the resubmission and earns a passing grade without penalty. This would be an example of a teachable moment. Student B turns in an assignment with a 25% match to another student’s paper on an online tutoring site. The faculty can obtain the matching paper, and the student admits to using the online resource but explains that they did not understand this was inappropriate. Student B is immediately given a zero for this assignment, which results in a course failure. Consider the following:
- Were these students treated fairly and consistently?
- Could student B appeal the outcome based on the grounds that they will now be financially responsible for retaking the course?
- Is there an appeal process in place at the school that allows the students to ask for a second look at their situation by an impartial third party?
- Should student B have been allowed to resubmit their assignment as well, due to their lack of understanding about the illicit use of a tutoring site? (Gallant, 2018)
These are all questions that arise in the day-to-day application of AI violations, sanctions, and the desire to be fair and consistent with all students to encourage growth and learning. Reasoning often cited by students include the likelihood that two people might paraphrase the same when using the same resources or articles. They may insist the work is their own, even where it is evident, they had outside help. If assignments are used year after year without updating, it is possible for TII or other anti-plagiarism software to erroneously flag similarities, simply because they are based on the use of the same pertinent articles or resources. In all accusations of wrongdoing, the burden of proof lies with the faculty. Professors should gather all evidence of plagiarism prior to confronting the student. The reports from TII, matching papers that can be downloaded, or exact text from websites offer evidence that can be difficult for the student to dispute. Faculty must determine if the match is due to the student having access to another student’s work and determine if the other student is involved in the violation even if not part of their own course (Gallant, 2018). To muddy the waters further, online tutoring services such as Course Hero allow students to “swap” (upload previous work in exchange for help in their current course). Their previous work is then used as a teaching guide, which current students may download without the original student being directly involved. Schools must determine hold accountable not only the student using the work but also the student who uploaded their work to an online site, allowing it to be used by others. School policies that describe all the potential violations that could be prosecuted, as well as evidence of distribution of the information to students, are the most consistent and fair for all involved (Garza-Mitchell & Parnther, 2018).
Part-time faculty may have additional difficulty in consistently recognizing and applying sanctions among students due to the extra time and effort required to detect and manage AI cases. The best practice for the management of AI violations is prevention through a strong code of conduct that is relayed to the students via live training or online activities that clearly delineate expectations. In order to adequately educate students, faculty should first be trained on the content and consistent application of the school’s policies across the curriculum. All students should be treated fairly with any incidents of plagiarism (Gallant, 2018; Goodwin & McCarthy, 2020). In February 2019, The University of Illinois at Chicago was required to pay $700,000 to a student after harming their reputation as well as career prospects due to false accusations of plagiarism. While this was a unique case, in which a professor openly accused the student of plagiarism in their dissertation, accusing anyone of plagiarism can lead to a defamation lawsuit to the faculty or school. Strong policies that are consistently applied to all individuals can decrease the risk for colleges and universities (Bailey, 2019).
The following case study may be helpful in considering how to apply AI violation policies fairly and consistently:
The university has a policy that students may not use any outside help while completing their online exams. The students are required to remain on camera throughout the exam, as well as use software that locks their web browser. Each class has a module called the “Academic Integrity Violation Module” that clearly defines all acts of cheating, including the use of their phone, another person, notes, or websites during their exam. Each student must sign an attestation each session, which states that they understand the implications of cheating on any exam or assignment. During an assignment in the third week, the professor views the exam videos, which are captured by software that flags any suspicious behavior (i.e., staying on a question too long, the student looking away from the camera repeatedly, or noises in the background). The faculty notices that Student A reads all their questions out loud during the test, then appears to look over their computer each time. This student takes longer to complete the test than the other students but earns 100% on the exam. When the professor initially reaches out to the student to inquire about reading the questions out loud, the student responds that they need this accommodation for testing.
The professor reports the student’s suspicious behavior to the program chair and sends a copy of the video. The professor also enquires about an individualized education program (IEP) with accommodations such as permission to read the exam out loud. The student does not have an IEP with any specific accommodations on file. The program chair determines that the student cheated on the exam and was talking out loud so that another individual could look up the answers. The student receives a course failure and is required to take the course again. However, this student is being paid to attend school by their employer, who requires a rationale for the failure. The student communicates the situation to their employer but denies cheating. This results in the student losing their employment due to the AI violation.
How can the faculty, department chair, and college ensure that they are not liable in the event of a defamation suit, or other legal allegations?
What steps should be in place to ensure the students’ rights are protected?
Case Study Answers:
How can the faculty, department chair, and college ensure that they are not liable in the event of a defamation suit, or other legal allegations?
Policies should be written that protect both students and faculty. The policies must be recognized by both students and faculty, and a written acknowledgment should be on file. For faculty, these policies should either be in the employee handbook or on their class contract to validate acceptance of their responsibility to properly apply the policy. Student information should be included in the syllabus, in their handbook, and/or in an AI module with a written acknowledgment of the institution/course policies related to AI. In this case, both the faculty and the program chair must document all details of the investigation, including the behaviors that led to their conclusion of cheating, a copy of the exam video, and any student/faculty communication related to the event. Further, it should be noted that the student was dishonest about having an IEP on file with accommodations related to online or campus testing. These steps should protect the school from any suits that could be filed. Careful protection of all individual’s private information must be considered during all AI sanctions; emails and databases must be protected by privacy software against breaches (Gallant, 2018; Goodwin & McCarthy, 2020).
What steps should be in place to ensure the students’ rights are protected?
All sanctions should include an appeals process that is reviewed by a neutral third party. In most institutions, there is a panel of faculty and leadership that reviews student appeal cases. Details regarding the appeals process should be included in the institution’s policy so that students are aware of their opportunities and rights. Once the appeals process is complete, documentation of all interactions should be added to the original file for the student involved (Gallant, 2018; Goodwin & McCarthy, 2020).
Babu, T. A., Joseph, N. M., Sharmila, V. (2011). Academic dishonesty among graduates from private medical schools in India. Medical Teacher, 33(9), 759-761. https://doi.org/ 10.3109/0142159X.2011.576717
Bailey, J. (2019). University settles with former student falsely accused of plagiarism. https://www.plagiarismtoday.com/2019/02/05/university-settles-with-former-student-falsely-accused-of-plagiarism/
Boston Globe. (2012). Harvard cheating scandal reveals gaps in costly education. https://www.bostonglobe.com/opinion/editorials/2012/09/06/harvard-cheating-scandal-reveals-gaps-costly-education/MPsyxJtBCm1PWWEf6ff1PP/story.html
The Center for Academic Integrity. (2014). The fundamental values, (2nd ed.). https://academicintegrity.org/wp-content/uploads/2017/12/Fundamental-Values-2014.pdf.
Douglas, S. & Watt, G. (2019). Plagiarism, academic integrity, and the law. eJournal of Business Education & Scholarship of Teaching, 13(2), 73-79. https://files.eric.ed.gov/fulltext/EJ1250484.pdf
Gallant, T. B. (2018). Part-time integrity? Contingent faculty and academic integrity. Promoting Academic Integrity, (183), 45-54. https://doi.org/10.1002/cc.20316
Garza-Mitchell, R. L. & Parnther, C. (2018). The shared responsibility for academic integrity. New Directions for Community Colleges, 183, 55-63. https://doi.org/ 10.1002/cc
Goodwin, J. & McCarthy, J. (2020). Explaining plagiarism for nursing students: An educational tool. Teaching and Learning in Nursing, 15(3), 198-203. https://doi.org/10.1016/j.teln.2020.03.004
Graham-Matheson, L. & Starr, S. (2013). Is it cheating – or learning the craft of writing? Using Turnitin to help students avoid plagiarism. Research in Learning Technology, 21. https://doi.org/10.3402/rlt.v21i0.17218
Henslee, A. M., Goldsmith, J., Stone, N. J. & Krueger, M. (2015). An online tutorial versus pre-recorded lecture for reducing incidents of plagiarism. American Journal of Engineering Education, 6(1), 27-32. https://clutejournals.com/index.php/AJEE/article/view/9249/9305
Krueger, L. (2014). Academic dishonesty among nursing students. Journal of Nursing Education.
53(2), 77-87. https://doi.org/ 10.3928/01484834-20140122-06
Orr, J. J. (2018). Developing a campus academic integrity education seminar. Journal of Academic Ethics, 16(3), 95-209. https://doi.org/10.1007/s10805-018-9304-7
Perez-Pena, R. & Bigood, J. (2012). Harvard says 125 students may have cheated on a final exam. [New York Times]. https://www.nytimes.com/2012/08/31/education/harvard-says-125-students-may-have-cheated-on-exam.html
Rani, P. S., Ravindran, V., Esther, A. A., Susilia, I. E., Charles, M., Rose, A., & Chacko, S. T. (2019). Nursing students’ perceptions and practices related to academic integrity. International Journal of Nursing Education, 11(3), 51-56. https://doi.org/10.5958/0974-9357.2019.00063.1
Reinhart, R. J. (2020). Nurses continue to rate highest in honesty, ethics. [Gallup]. https://news.gallup.com/poll/274673/nurses-continue-rate-highest-honesty-ethics.aspx
Rolfe, V. (2011). Can Turnitin be used to provide instant formative feedback? British Journal of Educational Technology, 42(4). https://doi.org/10.1111/j.1467-8535.2010.01091.x
Singh, S. & Remenyi, D. (2016). Plagiarism and ghostwriting: The rise in academic misconduct. South African Journal of Science, 112(5/6), 1-7. https://doi.org/ 10.17159/sajs.2016/20150300
Spezzo, V. (2018). From “I caught you!” to “I taught you!”: Using Turnitin to improve student writing. https://blog.ctl.gatech.edu/2018/11/08/from-i-caught-you-to-i-taught-you-using-turnitin-to-improve-student-writing/
St. Petersburg College. (n.d.). Plagiarism and academic dishonesty. Retrieved on September 28, 2020 from https://spcollege.libguides.com/c.php?g=254383&p=1695452#cheating